USGS Inorganic Blind Sample Project (IBSP)
Monitoring and Evaluating Laboratory Analytical Quality
(Based on Fact Sheet FS-136-97)
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he U.S. Geological
Survey (USGS) collects and disseminates information about the Nation's water
resources. Surface- and ground-water samples are collected and sent to USGS
laboratories for chemical analyses. The laboratories identify and quantify the
constituents in the water samples. Random and systematic errors occur during
sample handling, chemical analysis, and data processing. Although all errors
cannot be eliminated from measurements, the magnitude of this uncertainty can
be estimated and tracked over time. Since 1981, the USGS has operated an independent,
external, quality-assurance project called the Inorganic Blind Sample Project
(IBSP). The purpose of the IBSP is to monitor and evaluate the quality of laboratory
analytical results through the use of double-blind quality-control (QC) samples.
The information provided by the IBSP assists the laboratories in detecting and
correcting problems in the analytical procedures. The information also can aid
laboratory users in estimating the extent that laboratory errors contribute
to the overall errors in their environmental data.
A "double-blind sample" is a QC sample submitted for analysis for which
the identity of the sample as well as its concentration levels are unknown to
the analyst. Double-blind QC samples containing selected inorganic and nutrient
constituents at various levels of concentrations are prepared and disguised as
routine environmental samples. The IBSP submits these samples to the National
Water Quality Laboratory (NWQL) at the Denver Federal Center in Lakewood, CO.
The NWQL provides analytical services for all USGS national programs and many
local or regional projects conducted by the USGS.
Standard reference samples (Farrar and
Long, 1997) are used to make the QC samples for the IBSP. They are
used diluted with deionized water, undiluted, and mixed in
varying proportions with other standard reference samples. This
sample-mixing procedure produces a large number of unique samples
available for quality-assurance purposes. The standard reference
samples are usually natural matrix samples collected from
different sources such as snowmelt, streams, and ground water.
The IBSP samples are made to appear as
much like environmental samples as possible and are subjected to
identical laboratory handling, processing, and analytical
procedures. After the laboratories analyze the samples, IBSP
personnel compile and review the analytical results. The
resulting data are stored in the USGS National Water Information
System data base.
The laboratories are evaluated by how
closely their analytical results approximate the most probable
value of the blind QC samples. Most probable values are the
median concentrations reported for each constituent in the
round-robin evaluation of the standard reference sample. The
assessment of whether an analytical result is acceptable is based
on the number of standard deviations that the measured
concentration differs from the most probable value. Analytical
results that are within two standard deviations of the most
probable value are considered acceptable.
Analytical errors fall into two major
categories: bias and variability. Bias is systematic error that
causes consistently positive or negative deviation in the results
from the most probable value. Variability is random error that
affects the ability to reproduce results. Repeated measurements
of the IBSP samples over time provide estimates of both systematic
bias and random variability in the laboratory analytical
procedures. The IBSP uses a variety of graphical and statistical
tools to evaluate laboratory analyses of the blind QC samples.
These tools include control charts, relative standard deviation
charts, box plots of error distributions, Wilcoxon signed-rank
test for bias, binomial-probability distribution test for
variability, and statistical summaries.
Control charts are produced for each analytical method as a review of the
laboratory performance. They are a graphical display of the
analytical deviation from the most probable value with respect to
time. Control charts show if analytical results are within the
expected control limits. The IBSP sets control limits at ±2
standard deviations of the most probable value. These charts can
illustrate a systematic or sudden shift in bias or variability.
The control chart (fig. 1) for whole
water-recoverable iron analyses indicates a change from a positive
bias in February 1996 to a negative bias in September 1996.
Another graphical tool used by the IBSP
is the relative standard deviation chart, which displays
analytical variability with respect to concentration. These
charts allow a data reviewer to estimate analytical variability
at a given concentration. The relative standard deviation chart (fig. 2) for dissolved zinc analyses is
typical in showing that variability decreases with increasing
The IBSP maintains an interactive online computer program and data base (QADATA
Application) for the retrieval and assessment of blind QC sample analytical results.
Currently, the QADATA Application contains more than 235,000 QC analyses for inorganic
and nutrient constituents, and physical-property measurements dating from October
1984 to present. New analytical data released from the laboratories are added
twice-weekly to the QADATA Application. Data retrievals from the QADATA Application
can be customized to document the laboratories' analytical bias and variability
relative to the time period, analytical procedures, and concentration ranges of
individual water-quality projects or programs. The QADATA Application is available
through the USGS computing environment. For instructions on accessing and using
the QADATA Application contact Ted Struzeski at 303.236.1872 (email@example.com).
Farrar, J.W., and Long, H.K., 1997,
Report on the U.S. Geological Survey's evaluation program for
standard reference samples distributed in September 1996-T-143
(trace constituents), T-145 (trace constituents), M-140 (major
constituents), N-51 (nutrient constituents), N-52 (nutrient
constituents), P-27 (low ionic strength constituents), and Hg-23
(mercury): U.S. Geological Survey Open-File Report 97-20, 145 p.